In-Depth
BI 2012: The Future that has Already Happened
Eight current trends that yield insight into BI's future.
By Paul Sonderegger, Chief Strategist, Endeca Technologies, Inc.
Peter Drucker, godfather of business writing, had a terrific take on predictions: they're pointless. Instead, he recommended identifying major irrevocable events and prepare for their inevitable consequences (see Note 1). In other words, "prepare for the future that has already happened."
This is good advice when it comes to the future of BI. The major factors affecting BI's future are already in play. Looking over the BI landscape today, we find one factor that dominates, big data, and a host of others along for the ride – pervasive, agile, mobile, social, fast, easy and cheap. It's Snow White and the seven dwarves of BI market trends:
Big data is the big deal. The world is busily creating a digital copy of itself one transaction, tweet, and post at a time. The geometric growth rate of this data means an effectively endless supply of information to analyze. However, volume is not the big story in big data -- variety is. Companies will have to adopt new technologies to bring down the time, effort, and cost of integrating large amounts of diverse and changing data beyond the warehouse. They'll have to experiment with new user experiences to reduce the time and effort for the user to understand all that information to make better choices.
Pervasive. Analytics are now a part of everyday life. For example, Amazon.com tells you what percentage of people who looked at the same product as you actually bought it. Yelp's rating trend charts show not just a restaurant's average rating, but the trend in its rating over time. Countless mobile apps help you track the calories you consume and analyze how far off the mark you are.
Agile. The interconnectedness of our global economy has increased market volatility. This effect is most pronounced on the biggest adopters of IT. Since the mid-1990s, the turbulence (average jump in number of places up or down the top 10 ranking, by sales) of high IT-adopting industries has increased, driving a need for greater agility (see Note 2).
Mobile. There are now 835 million smartphone users in the world. More important is that there are 5.6 billion mobile phone users in total, with smartphones steadily gaining share (see Note 3). This explains why Apple recently announced that 93 percent of Fortune 500 firms are testing and deploying iPhones; the figure is 92 percent for iPads (see Note 4).
Social. The vague, complicated idea of collaborative software has become the specific, simple idea of social networking. If Facebook's 800 million users were a nation, they would be the third most populous country in the world. This ubiquity has given rise to a host of work-specific social networks from big enterprise software players as well as newcomers, which will change the way corporate decision-making works
Fast. Multi-core, big-memory servers and cloud-based analytical services make commodity supercomputing affordable for more companies than ever before, allowing them to crunch more data than ever before.
Easy. The increase of so-called digital natives (those who have grown up with always-on access to the Internet) in the workforce intensifies the demand for easy-to-use enterprise software and increases the penalty for firms that ignore them.
Cheap. The growing acceptance of SaaS and open source software among enterprise IT pros increases price pressure for the commoditized aspects of BI like reporting, scorecards and dashboards. In addition, the success of inexpensive, straight-to-the-desktop data discovery tools has shown business analysts that good things can come with small price tags.
These accomplished facts have implications for the future of BI:
Unstructured data comes in from the cold. Long considered the poor cousin of warehouse data, unstructured data (such as social media, e-mail, and documents) will increasingly show up in BI apps. The irony is that this will happen by adding a great variety of structure. Text analytics techniques such as entity extraction, sentiment analysis, and automatic classification turn implicit structure into a huge variety of explicit fielded data that can't be handled effectively by traditional, relational BI technologies.
Hadoopers and NoSQLists take to the streets. The clash between relational and post-relational technologies will heat up. As the cloud gains acceptance, key-value stores such as Cassandra and commercializations of Hadoop will take their place alongside the traditional warehouse. Expect a hotbed of innovation in this space as upstarts try to differentiate against big incumbents who are integrating Hadoop into their existing offerings.
A thousand analytical flowers bloom. Analytics will be everywhere. They'll be embedded in traditional enterprise applications such as ERP and CRM, blurring the line between process apps and BI. The operational nature of many of these analytics will complement BI's traditional single version of the truth with "ground" truth -- BI will finally fulfill its promise of providing both authoritative metrics for executives as well as on-the-ground measures for frontline personnel.
Data exhaust creates a first-mover advantage. As analyses on more kinds of data become faster and easier, the value of having more kinds of data goes up. Companies that gather and scrutinize a greater diversity of customer interaction data will improve their understanding of customer needs and improve the quality of their offerings, creating a virtuous cycle rivals will find difficult to break.
A Final Thought
These are not predictions. In Drucker's words, "these are the implications of a future which has already happened."
NOTES:
1. The Future That Has Already Happened, Peter Drucker, The FUTURIST Magazine, November 1998.
2. Investing in the IT That Makes a Competitive Difference, Andrew McAfee and Erik Brynjolfsson, Harvard Business Review, July 2008.
3. Presentation by Mary Meeker of Kleiner Perkins Caulfield Byers.
4. Once Wary, Apple Warms Up to Business Market, The New York Times, Nov 15, 2011.
Paul Sonderegger is chief strategist at Endeca. He helps global organizations turn big data into better daily decisions to gain competitive advantage. Previously, Paul was a Principal Analyst at Forrester Research, where he published numerous reports on enterprise search and user experience, and advised hundreds of executives at Global 2000 firms. You can contact the author at [email protected]
.